As a data scientist, our work does not stop at machine learning model training alone. We definitely need to do more than that.  

It is similar to the forward or striker in a soccer match, preparing to strike the ball towards goal…you still have not done the most important step yet and that is to score the goal!

So what is needed to score the “goal”? Translate that insights into tangible benefits, either protect/increase revenue, and or reduce costs.

For instance, customer turnover analysis. If you stop at just providing the  best machine learning model, you are only able to provide the behavior profile of customer likely to turnover, you still have not worked on understanding the reason why they might be leaving…which of course the model may provide some clues but you’ll need to dig somewhere else to  understand further.

Remember, as a data scientist, one of our main responsibilities is turning our insights into something tangible and not just stopping at insights only. :)

What are your thoughts? Will love to hear them!

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